Home // SIMUL 2014, The Sixth International Conference on Advances in System Simulation // View article
Authors:
Li Gu
C. F. Jeff Wu
Keywords: Uncertainty analysis; Sensitivity analysis; Screening; Effect hierarchy principle; Effect heredity principle; Polynomial chaos expansions.
Abstract:
Computational models have found wide applications in simulating physical systems. Uncertainties in input parameters of the system can greatly influence the outputs, which are studied by Uncertainty Analysis (UA) and Sensitivity Analysis (SA). As the system becomes more complex, the number of input parameters can be large and existing methods for UA and SA are computationally intensive or prohibitive. We propose a unified framework by using a hierarchical variable selection approach to connect UA and SA with one design. By incorporating the effect hierarchy principle and the effect heredity principle, the method works well especially when the number of input parameters is large. Since the procedure requires only one design, it is economical in run size and computationally efficient.
Pages: 276 to 280
Copyright: Copyright (c) IARIA, 2014
Publication date: October 12, 2014
Published in: conference
ISSN: 2308-4537
ISBN: 978-1-61208-371-1
Location: Nice, France
Dates: from October 12, 2014 to October 16, 2014